The global AI in healthcare market size was estimated at USD 19.27 billion in 2023 and is expected to grow at a CAGR of 38.5% from 2024 to 2030. One primary factor driving market growth is the increasing demand in the healthcare sector for enhanced efficiency, accuracy, and better patient outcomes. According to a March 2024 Microsoft-IDC study, 79% of healthcare organizations are presently utilizing AI technology. In addition, the return on investment (ROI) is realized within 14 months, generating USD 3.20 for every USD 1 invested in artificial intelligence (AI). AI technologies hold transformative potential in various areas including medical imaging analysis, predictive analytics, personalized treatment planning, and drug discovery, potentially transforming conventional healthcare practices.
The exponential growth in healthcare data, sourced from electronic health records (EHRs), medical imaging scans, wearable devices, and genomic sequencing, presents significant opportunities for AI-powered solutions to extract actionable insights and support clinical decision-making. The shortage of healthcare workers is also driving the adoption of AI and machine learning (ML) technologies. According to the World Economic Forum estimates from May 2023, there will be a global health worker deficit of 10 million by 2030. Hence, AI algorithms can be trained to analyze patient health data, aiding care providers in rapid diagnosis and treatment planning. Supportive government initiatives and the COVID-19 impact along with a rise in technological collaborations & M&A activities have contributed to the market's growth and accelerated the adoption of AI in healthcare.
AI and ML algorithms are increasingly being used for rapid and accurate diagnosis, including the detection of COVID-19-positive cases using personalized patient data. For instance, a 2020 NCBI study found that AI-based algorithms accurately detected 68% of COVID-19-positive cases in a dataset of 25 patients initially diagnosed as negative by healthcare professionals. The implementation of AI and ML technologies aims to enhance patient care, reduce machine downtime, and lower care expenses, driving market growth. The pandemic has further accelerated the adoption of AI-based technologies, particularly in diagnostics, patient and medication management, claims processing, workflow optimization, machine integration, and cybersecurity within healthcare settings.
The Healthcare AI market exhibits a high degree of innovation, characterized by ongoing advancements in technology. Rapid developments in ML, deep learning, NLP, and computer vision are driving the evolution of AI-powered healthcare solutions. For instance, in June 2023, Saama introduced two innovative ML and AI-based solutions for clinical trials
Mergers & acquisitions (M&As) play a significant role in shaping the healthcare AI market landscape. Companies engage in M&A activities to expand their AI software and services, increase their market reach, or acquire specialized technology and expertise. For example, in January 2023, GE Healthcare acquired MIM Software Inc., a provider of AI-based imaging analysis software for radiology
Regulations, such as the Health Insurance Portability & Accountability Act (HIPAA), in the United States and General Data Protection Regulation (GDPR) in Europe establish standards for safeguarding patient data privacy and security. Compliance with these regulations is crucial for AI applications in healthcare to ensure the safe and secure handling of patient information, reducing the risk of data breaches and unauthorized access
The threat of substitute products in the market is anticipated to be low. While alternative technologies or approaches may serve as substitutes in specific AI applications within healthcare, their capabilities often differ from AI-driven solutions. For example, in drug discovery, traditional R&D methods may be utilized instead of AI-driven algorithms for identifying potential drug candidates. Similarly, wearable devices and IoT sensors offer alternative means of gathering patient data for monitoring and diagnosis, but they typically lack the advanced analytical capabilities inherent in AI systems
End-users are becoming increasingly aware of the potential benefits of AI in improving patient care, operational efficiency, and healthcare outcomes. Education initiatives and industry events helped raise awareness about the capabilities and applications of AI in healthcare
The software solution component segment is anticipated to grow at the fastest CAGR of 38.7% over the forecast period. The segment growth is attributed to the rapidly growing adoption of AI-based software solutions among healthcare providers, payers, and patients. For instance, in September 2019, GE Healthcare partnered with five Chinese local software developers namely, 12Sigma Technologies, Biomind, Shukun Technology, Yizhun Medical AI, and YITU Technology to collaboratively work on developing the Edison AI platform and support the smooth digital transformation of GE Healthcare.
The services component segment is anticipated to witness significant growth from 2024 to 2030. The growth of this segment can be attributable to the rising penetration of AI-based technologies in several healthcare applications, such as clinical trials, virtual assistants, robot-assisted surgeries, dosage error reduction, and fraud detection.
The M) technology segment held the largest share in 2023. The healthcare industry generates vast amounts of data, including EHRs, medical imaging, genomic data, and wearable device data. Machine learning excels at extracting valuable insights from these large and diverse datasets, enabling healthcare providers to make data-driven decisions and improve patient outcomes. This technology is extensively integrated into healthcare solutions for disease diagnosis, prognosis, and treatment planning. Leveraging patient data patterns and correlations, ML models can detect early disease indicators, forecast patient outcomes, and propose personalized treatment strategies, thereby enhancing the accuracy and timeliness of interventions.
The natural language processing (NLP) technology segment is expected to grow at a significant CAGR from 2024 to 2030. Natural language processing facilitates the automation and optimization of clinical documentation processes, such as medical transcription, coding, and charting. By automatically extracting and coding relevant information from clinical narratives, NLP accelerates documentation workflows, reduces administrative burden, and ensures accuracy in billing and reimbursement.
The robot-assisted surgery application segment dominated the market in 2023 with the largest revenue share and is anticipated to witness significant CAGR growth from 2024 to 2030. A rise in the volume of robot-assisted surgeries and increased funding and investment in AI platform development are key drivers propelling AI penetration in this field. For instance, according to a May 2023 Nasdaq, Inc. article, Intuitive Surgical, a leading surgical robotics provider, reported robust Q1 2023 results, with revenue up by 14% YoY to USD 1.7B, driven by a 26% growth in robotics procedures, surpassing expectations by 12 points.
Moreover, the placement of 312 systems exceeded expectations. In addition, the establishment of the Clinical Robotic Surgery Association in India in August 2019 underscores the growing demand for robotic surgeries and the need for trained professionals in this domain. The anticipated rise in AI adoption is attributed to the shortage of skilled surgeons.
The healthcare companies segment dominated the market with the largest revenue share in 2023. The widespread adoption of AI technologies in drug development, leveraging genomic information, medical records, and clinical trial data, enables the identification of personalized treatment options and the targeting of therapies to specific patient groups. AI-driven analytics and predictive modeling improve the design, execution, and analysis of clinical trials, resulting in more efficient and cost-effective trials. As per a study by Scilife N.V. in January 2024, approximately 80% of professionals in the pharmaceutical and life sciences sectors utilize AI in drug discovery. Furthermore, research from another study suggests that AI technology reduces the time required by pharmaceutical companies to discover new drugs from 5-6 years to just one year.
The healthcare providers (hospitals, outpatient facilities, and others) segment is expected to grow significantly over the forecast period. AI-powered medical imaging analysis tools aid healthcare providers in interpreting medical images like X-rays, MRIs, and CT scans. These tools improve diagnostic accuracy, shorten interpretation time, and facilitate early disease detection, resulting in prompt interventions and enhanced patient care. In addition, hospitals are leveraging AI-driven predictive analytics to anticipate patient admission rates, pinpoint at-risk populations, and allocate resources effectively. These factors are driving the segment growth.
North America AI in healthcare market accounted for the largest revenue share of over 45% in 2023. This can be attributed to advancements in healthcare IT infrastructure, growing care expenditures, widespread adoption of AI/ML technologies, favorable government initiatives, lucrative funding options, and the presence of several key players. Factors, such as growing geriatric population, changing lifestyles, increasing prevalence of chronic disorders, growing demand for value-based care, and rising awareness levels about the implementation of AI-based technologies are further propelling market growth in North America.
AI in healthcare market in the U.S. held the largest market share in 2023 due to increased demand for efficient and personalized healthcare solutions, coupled with advancements in AI research and development-especially in ML and NLP-alongside regulatory initiatives and supportive policies.
Europe AI in healthcare market is anticipated to witness significant growth. This can be attributed to the widespread adoption of AI technologies and increasing investments in AI by both government and private organizations. For example, in 2021, the Department of Health and Social Care in Europe allocated USD 49.3 (£36 million) across thirty-eight AI initiatives aimed at enhancing patient care and expediting diagnosis.
AI in healthcare market in the UK held the largest share in 2023. AI applications are becoming increasingly prevalent in healthcare, particularly in areas, such as medical imaging analysis, predictive analytics, and personalized treatment planning. The UK's National Health Service (NHS) is actively exploring AI technologies to enhance patient care, optimize operations, and tackle various healthcare challenges.
Asia Pacific AI in healthcare market is projected to experience significant growth in the coming years. This growth is fueled by rapid innovations and advancements in IT infrastructure, as well as the emergence of entrepreneurship ventures specializing in AI-based technologies. Increasing investments from private investors, venture capitalists, and non-profit organizations aimed at enhancing clinical outcomes, improving data analysis and security, and reducing costs are driving adoption rates in the region. In addition, favorable government initiatives that support and promote the adoption of AI-based technologies by healthcare organizations and providers are anticipated to boost market growth.
AI In Healthcare market in China held the largest share in 2023 due to the increased adoption of AI technologies for diagnosis, medical imagining, and robot-assisted surgeries in the country. For example, in 2019, Partners Healthcare collaborated with FUJIFILM Sonosite to develop AI-based ultrasound technology. This collaboration was aimed at enhancing accessibility to healthcare technology and improving the quality of diagnostic care provided to patients.
Latin America AI In Healthcare market is anticipated to grow significantly in the coming years. This can be attributed to the growing awareness about AI technologies, increasing government spending, and collaboration activities.
AI in healthcare market in Middle East & Africa is anticipated to grow significantly during the forecast period. The rising prevalence of chronic diseases in the region and growing need for efficient & accurate diagnosis and treatment methods are prompting healthcare providers to integrate AI into their systems.
Market players are utilizing innovative product development strategies, partnerships, and mergers and acquisitions to expand their presence in response to the increasing demand for early and accurate disease detection, cost containment, addressing the shortage of healthcare providers, and providing value-based care.
AI Startup Ecosystem:
The AI healthcare industry is teeming with startups driven by the funding, investment and innovations. These startups leverage AI and machine learning to address various healthcare challenges, from medical imaging and diagnostics to drug discovery and telemedicine.
Some of the key insights on the AI start up ecosystem:
The following are the leading companies in the AI in healthcare market. These companies collectively hold the largest market share and dictate industry trends.
In March 2024, Microsoft collaborated with NVIDIA to enhance AI innovation and accelerate computing capabilities. This collaboration leverages Microsoft Azure's global scale and advanced computing along with NVIDIA’s DGX Cloud and Clara suite to accelerate innovation and improve patient care
“Microsoft is building on its longstanding collaboration with NVIDIA to empower the healthcare and life sciences industry with the power of Azure and generative AI, helping unlock new horizons for clinical research, drug discovery, and patient care worldwide. Through this collaboration, we aim to help the industry unlock breakthroughs in healthcare, making care more precise, accessible, and effective to deliver a meaningful difference in the lives of patients globally.”
- Peter Durlach, corporate vice president, Health & Life Sciences, Microsoft
In March 2024, NVIDIA introduced new Generative AI Microservices to transform medical technology (MedTech), drug discovery, and digital health. This innovative approach aims to reshape healthcare technology by harnessing advanced AI capabilities
“For the first time in history, we can represent the world of biology and chemistry in a computer, making computer-aided drug discovery possible. By helping healthcare companies easily build and manage AI solutions, we’re enabling them to harness the full power and potential of generative AI.”
- Kimberly Powell, vice president of healthcare at NVIDIA
In September 2023, Merck KGaA entered into a strategic collaboration with Exscientia and BenevolentAI to drive accelerated drug discovery with the integration of high-end AI platforms
Report Attribute |
Details |
The market size value in 2024 |
USD 26.6 billion |
The revenue forecast in 2030 |
USD 187.7 billion |
Growth rate |
CAGR of 38.5% from 2024 to 2030 |
The base year for estimation |
2023 |
Historical data |
2018 - 2022 |
Forecast period |
2024 - 2030 |
Report updated |
April 2024 |
Quantitative units |
Revenue in USD million and CAGR from 2024 to 2030 |
Report coverage |
Revenue, company ranking, competitive landscape, growth factors, and trends |
Segments covered |
Component, application, technology, end-user, and region |
Regional scope |
North America; Europe; Asia Pacific; Latin America; MEA |
Country scope |
U.S.; Canada; Germany; UK; Spain; France; Italy; Sweden; Denmark; Norway; Russia; Japan; China; India; South Korea; Australia; Singapore; Thailand; Brazil; Mexico; Argentina; South Africa; Saudi Arabia; UAE; Kuwait |
Key companies profiled |
Microsoft; IBM; NVIDIA Corp.; Intel Corp.; Itrex Group; GE Healthcare; Google; Medtronic; Oracle; Medidata; Merck; IQVIA |
Customization scope |
Free report customization (equivalent up to 8 analysts working days) with purchase. Addition or alteration to country, regional & segment scope |
Pricing and purchase options |
Avail customized purchase options to meet your exact research needs. Explore purchase options |
This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest trends in each of the sub-segments from 2018 to 2030. For this study, Grand View Research, Inc. has segmented the global AI in healthcare market report based on component, application, technology, end-use, and region:
Component Outlook (Revenue, USD Million, 2018 - 2030)
Hardware
Processor
MPU (Memory Protection Unit)
FPGA (Field-programmable Gate Array)
GPU (Graphics Processing Unit)
ASIC (Application-specific Integrated Circuit)
Memory
Network
Adapter
Interconnect
Switch
Software Solutions
AI platform
Application Program Interface (API)
Machine Learning Framework
AI Solutions
On-premise
Cloud-based
Services
Deployment & Integration
Support & Maintenance
Others (Consulting, Compliance Management, etc.)
Application Outlook (Revenue, USD Million, 2018 - 2030)
Robot-assisted Surgery
Virtual Assistants
Administrative Workflow Assistants
Connected Medical Devices
Medical Imaging & Diagnostics
Clinical Trials
Fraud Detection
Cybersecurity
Dosage Error Reduction
Precision Medicine
Drug Discovery & Development
Lifestyle Management & Remote Patient Monitoring
Wearables
Others (Patient Engagement, etc.)
Technology Outlook (Revenue, USD Million, 2018 - 2030)
Machine Learning
Deep Learning
Supervised
Unsupervised
Others (Reinforcement Learning, Semi-supervised)
Natural Language Processing
Smart Assistance
OCR (Optical Character Recognition)
Auto Coding
Text Analytics
Speech Analytics
Classification & Categorization
Context-aware Computing
Computer Vision
End-use Outlook (Revenue, USD Million, 2018 - 2030)
Healthcare Providers (Hospitals, Outpatient Facilities, and Others)
Healthcare Payers
Healthcare Companies (Pharmaceutical, Biotechnology, Medical Devices)
Patients
Others
Regional Outlook (Revenue, USD Million, 2018 - 2030)
North America
U.S.
Canada
Europe
UK
Germany
France
Italy
Spain
Sweden
Denmark
Norway
Russia
Asia Pacific
China
India
Japan
Australia
Singapore
South Korea
Thailand
Latin America
Brazil
Mexico
Argentina
MEA
South Africa
Saudi Arabia
UAE
Kuwait
b. North America dominated AI in healthcare market and accounted for the largest revenue share of 57.7% in 2023.
b. Some key players operating in the AI in healthcare market include IBM Corporation; NVIDIA Corporation; Nuance Communications, Inc.; Microsoft; Intel Corporation; and DeepMind Technologies Limited.
b. Key factors that are driving the AI in healthcare market growth include the growing need for lowering healthcare costs, the growing importance of big data in healthcare, the rising adoption of precision medicine, and declining hardware costs.
b. The global artificial intelligence in healthcare market size was estimated at USD 19.27 billion in 2023 and is expected to reach USD 26.6 billion in 2024.
b. The global AI in healthcare market is expected to grow at a compound annual growth rate of 38.5% from 2024 to 2030 to reach USD 187.7 billion by 2030.
Table of Contents
Chapter 1. Methodology and Scope
1.1. Market Segmentation & Scope
1.2. Research Methodology
1.3. Information Procurement
1.3.1. Purchased database
1.3.2. GVR’s internal database
1.3.3. Secondary sources
1.3.4. Primary research
1.3.5. Details of primary research
1.3.5.1. Data for primary interviews in North America
1.3.5.2. Data for primary interviews in Europe
1.3.5.3. Data for primary interviews in Asia Pacific
1.3.5.4. Data for primary interviews in Latin America
1.3.5.5. Data for Primary interviews in MEA
1.4. Information or Data Analysis
1.4.1. Data analysis models
1.5. Market Formulation & Data Validation
1.6. Model Details
1.6.1. Commodity flow analysis (Model 1)
1.6.2. Approach 1: Commodity flow approach
1.6.3. Volume price analysis (Model 2)
1.6.4. Approach 2: Volume price analysis
1.7. List of Secondary Sources
1.8. List of Primary Sources
1.9. Objectives
Chapter 2. Executive Summary
2.1. Market Outlook
2.2. Segment Outlook
2.2.1. Component outlook
2.2.2. Application outlook
2.2.3. Technology outlook
2.2.4. End-Use outlook
2.2.5. Regional outlook
2.3. Competitive Insights
Chapter 3. Artificial Intelligence (AI) In Healthcare Market Variables, Trends & Scope
3.1. Market Lineage Outlook
3.1.1. Parent market outlook
3.1.2. Related/ancillary market outlook
3.2. Market Dynamics
3.2.1. Market driver analysis
3.2.2. Market restraint analysis
3.2.3. Market opportunity analysis
3.2.4. Market challenges analysis
3.3. Case Studies: Real-World Implementation Success Stories of AI-Driven Healthcare
3.4. AI In Healthcare Market Analysis Tools
3.4.1. Industry Analysis - Porter’s
3.4.1.1. Supplier power
3.4.1.2. Buyer power
3.4.1.3. Substitution threat
3.4.1.4. Threat of new entrant
3.4.1.5. Competitive rivalry
3.4.2. PESTEL Analysis
3.4.2.1. Political landscape
3.4.2.2. Technological landscape
3.4.2.3. Economic landscape
3.4.2.4. Environmental Landscape
3.4.2.5. Legal Landscape
3.4.2.6. Social Landscape
3.4.3. Industry Analysis - COVID-19 impact
Chapter 4. Artificial Intelligence (AI) In Healthcare Market: Component Estimates & Trend Analysis
4.1. Definitions and Scope
4.2. Segment Dashboard
4.3. AI In Healthcare Market Movement Analysis
4.4. AI In Healthcare Market Size & Trend Analysis by Component, 2018 to 2030 (USD Million)
4.4.1. Software Solutions
4.4.1.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.1.1.1. AI platform
4.4.1.1.1.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.1.1.1.2. Application Program Interface (API)
4.4.1.1.1.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.1.1.1.3. Machine Learning Framework
4.4.1.1.1.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.1.1.2. AI Solutions
4.4.1.1.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.1.1.2.2. On premise
4.4.1.1.2.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.1.1.2.3. Cloud based
4.4.1.1.2.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.2. Hardware
4.4.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.2.1.1. Processor
4.4.2.1.1.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.2.1.1.2. MPU (memory protection unit)
4.4.2.1.1.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.2.1.1.3. FPGA (Field-programmable gate array)
4.4.2.1.1.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.2.1.1.4. GPU (Graphics processing unit)
4.4.2.1.1.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.2.1.1.5. ASIC (Application-specific integrated circuit)
4.4.2.1.1.5.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.2.1.2. Memory
4.4.2.1.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.2.1.3. Network
4.4.2.1.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.2.1.3.2. Adapter
4.4.2.1.3.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.2.1.3.3. Interconnect
4.4.2.1.3.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.2.1.3.4. Switch
4.4.2.1.3.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.3. Services
4.4.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.3.1.1. Deployment & Integration
4.4.3.1.1.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.3.1.2. Support & Maintenance
4.4.3.1.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.3.1.3. Others (Consulting, Compliance management etc.)
4.4.3.1.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.4. Distributed Denial of Service (DDoS) Mitigation
4.4.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.5. Security Information and Event Management
4.4.5.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.6. Intrusion Detection System (IDS)/Intrusion Prevention System (IPS)
4.4.6.1. Market estimates and forecast 2018 to 2030 (USD Million)
4.4.7. Others
4.4.7.1. Market estimates and forecast 2018 to 2030 (USD Million)
Chapter 5. Artificial Intelligence (AI) In Healthcare Market: Application Estimates & Trend Analysis
5.1. Definitions and Scope
5.2. Segment Dashboard
5.3. AI In Healthcare Market Movement Analysis
5.4. AI In Healthcare Market Size & Trend Analyses, by Application, 2018 to 2030 (USD Million)
5.4.1. Robot-assisted Surgery
5.4.1.1. Market estimates and forecast 2018 to 2030 (USD Million)
5.4.2. Virtual Assistants
5.4.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
5.4.3. Administrative Workflow Assistants
5.4.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
5.4.4. Connected Medical Devices
5.4.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
5.4.5. Medical Imagining & Diagnosis
5.4.5.1. Market estimates and forecast 2018 to 2030 (USD Million)
5.4.6. Clinical Trials
5.4.6.1. Market estimates and forecast 2018 to 2030 (USD Million)
5.4.7. Fraud Detection
5.4.7.1. Market estimates and forecast 2018 to 2030 (USD Million)
5.4.8. Cybersecurity
5.4.8.1. Market estimates and forecast 2018 to 2030 (USD Million)
5.4.9. Dosage Error Reduction
5.4.9.1. Market estimates and forecast 2018 to 2030 (USD Million)
5.4.10. Precision Medicine
5.4.10.1. Market estimates and forecast 2018 to 2030 (USD Million)
5.4.11. Drug Discovery & Development
5.4.11.1. Market estimates and forecast 2018 to 2030 (USD Million)
5.4.12. Lifestyle Management & Remote Patient Monitoring
5.4.12.1. Market estimates and forecast 2018 to 2030 (USD Million)
5.4.13. Wearables
5.4.13.1. Market estimates and forecast 2018 to 2030 (USD Million)
5.4.14. Others
5.4.14.1. Market estimates and forecast 2018 to 2030 (USD Million)
Chapter 6. Artificial Intelligence (AI) In Healthcare Market: Technology Estimates & Trend Analysis
6.1. Definitions and Scope
6.2. Segment Dashboard
6.3. AI In Healthcare Market Movement Analysis
6.4. AI In Healthcare Market Size & Trend Analyses, by Technology, 2018 to 2030 (USD Million)
6.4.1. Machine Learning
6.4.1.1. Market estimates and forecast 2018 to 2030 (USD million)
6.4.1.1.1. Deep learning
6.4.1.1.1.1. Market estimates and forecast 2018 to 2030 (USD Million)
6.4.1.1.2. Supervised
6.4.1.1.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
6.4.1.1.3. Unsupervised
6.4.1.1.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
6.4.1.1.4. Others (Reinforcement learning, Semi supervised)
6.4.1.1.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
6.4.2. NLP
6.4.2.1. Market estimates and forecast 2018 to 2030 (USD million)
6.4.2.1.1. Smart Assistance
6.4.2.1.1.1. Market estimates and forecast 2018 to 2030 (USD Million)
6.4.2.1.2. OCR (Optical Character Recognition)
6.4.2.1.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
6.4.2.1.3. Auto Coding
6.4.2.1.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
6.4.2.1.4. Text analytics
6.4.2.1.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
6.4.2.1.5. Speech analytics
6.4.2.1.5.1. Market estimates and forecast 2018 to 2030 (USD Million)
6.4.2.1.6. Classification and categorization
6.4.2.1.6.1. Market estimates and forecast 2018 to 2030 (USD Million)
6.4.3. Computer Vision
6.4.3.1. Market estimates and forecast 2018 to 2030 (USD million)
6.4.4. Context-aware Computing
6.4.4.1. Market estimates and forecast 2018 to 2030 (USD million)
Chapter 7. Artificial Intelligence (AI) In Healthcare Market: End-use Estimates & Trend Analysis
7.1. Definitions and Scope
7.2. Segment Dashboard
7.3. AI In Healthcare Market Movement Analysis
7.4. AI In Healthcare Market Size & Trend Analyses, By End-Use, 2018 to 2030 (USD Million)
7.4.1. Healthcare Providers (Hospitals, Outpatient Facilities, and Others)
7.4.1.1. Market estimates and forecast 2018 to 2030 (USD million)
7.4.2. Healthcare Payers
7.4.2.1. Market estimates and forecast 2018 to 2030 (USD Million)
7.4.3. Healthcare Companies
7.4.3.1. Market estimates and forecast 2018 to 2030 (USD Million)
7.4.4. Patients
7.4.4.1. Market estimates and forecast 2018 to 2030 (USD Million)
7.4.5. Others
7.4.5.1. Market estimates and forecast 2018 to 2030 (USD Million)
Chapter 8. Artificial Intelligence (AI) In Healthcare Market: Regional Estimates & Trend Analysis by Component, Application, Technology & End-use
8.1. Regional Market Dashboard
8.2. Global Regional Market Snapshot
8.3. Market Size, & Forecasts Trend Analysis, 2018 to 2030
8.4. North America
8.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
8.4.2. U.S.
8.4.2.1. U.S. market estimates and forecast, 2018 - 2030 (USD Million)
8.4.3. Canada
8.4.3.1. Canada market estimates and forecast, 2018 - 2030 (USD Million)
8.5. Europe
8.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)
8.5.2. UK
8.5.2.1. UK market estimates and forecast, 2018 - 2030 (USD Million)
8.5.3. Germany
8.5.3.1. Germany market estimates and forecast, 2018 - 2030 (USD Million)
8.5.4. France
8.5.4.1. Germany market estimates and forecast, 2018 - 2030 (USD Million)
8.5.5. Italy
8.5.5.1. Germany market estimates and forecast, 2018 - 2030 (USD Million)
8.5.6. Spain
8.5.6.1. Germany market estimates and forecast, 2018 - 2030 (USD Million)
8.5.7. Sweden
8.5.7.1. Germany market estimates and forecast, 2018 - 2030 (USD Million)
8.5.8. Denmark
8.5.8.1. Germany market estimates and forecast, 2018 - 2030 (USD Million)
8.5.9. Norway
8.5.9.1. Germany market estimates and forecast, 2018 - 2030 (USD Million)
8.5.10. Russia
8.5.10.1. Germany market estimates and forecast, 2018 - 2030 (USD Million)
8.6. Asia Pacific
8.6.1. Market estimates and forecasts 2018 to 2030 (USD Million)
8.6.2. Japan
8.6.2.1. Japan market estimates and forecast, 2018 - 2030 (USD Million)
8.6.3. China
8.6.3.1. China market estimates and forecast, 2018 - 2030 (USD Million)
8.6.4. India
8.6.4.1. China market estimates and forecast, 2018 - 2030 (USD Million)
8.6.5. Singapore
8.6.5.1. China market estimates and forecast, 2018 - 2030 (USD Million)
8.6.6. Australia
8.6.6.1. China market estimates and forecast, 2018 - 2030 (USD Million)
8.6.7. South Korea
8.6.7.1. China market estimates and forecast, 2018 - 2030 (USD Million)
8.6.8. Thailand
8.6.8.1. China market estimates and forecast, 2018 - 2030 (USD Million)
8.7. Latin America
8.7.1. Market estimates and forecasts 2018 to 2030 (USD Million)
8.7.2. Brazil
8.7.2.2. Brazil market estimates and forecast, 2018 - 2030 (USD Million)
8.7.3. Mexico
8.7.3.2. Mexico market estimates and forecast, 2018 - 2030 (USD Million)
8.7.4. Argentina
8.7.4.1. China market estimates and forecast, 2018 - 2030 (USD Million)
8.8. MEA
8.8.1. Market estimates and forecasts 2018 to 2030 (USD Million)
8.8.2. South Africa
8.8.2.1. South Africa market estimates and forecast, 2018 - 2030 (USD Million)
8.8.3. Saudi Arabia
8.8.3.1. Saudi Arabia market estimates and forecast, 2018 - 2030 (USD Million)
8.8.4. UAE
8.8.4.1. China market estimates and forecast, 2018 - 2030 (USD Million)
8.8.5. Kuwait
8.8.5.1. China market estimates and forecast, 2018 - 2030 (USD Million)
Chapter 9. Competitive Landscape
9.1. Recent Developments & Impact Analysis, By Key Market Participants
9.2. Company/Competition Categorization
9.2.1. Key Innovators
9.2.2. Market Leaders
9.2.3. Emerging Players
9.3. Vendor Landscape
9.3.1. Key company market share analysis, 2023
9.3.2. Microsoft
9.3.2.1. Company overview
9.3.2.2. Financial performance
9.3.2.3. Product benchmarking
9.3.2.4. Strategic initiatives
9.3.3. IBM
9.3.3.1. Company overview
9.3.3.2. Financial performance
9.3.3.3. Product benchmarking
9.3.3.4. Strategic initiatives
9.3.4. NVIDIA Corporation
9.3.4.1. Company overview
9.3.4.2. Financial performance
9.3.4.3. Product benchmarking
9.3.4.4. Strategic initiatives
9.3.5. Intel Corporation
9.3.5.1. Company overview
9.3.5.2. Financial performance
9.3.5.3. Product benchmarking
9.3.5.4. Strategic initiatives
9.3.6. Itrex Group
9.3.6.1. Company overview
9.3.6.2. Financial performance
9.3.6.3. Product benchmarking
9.3.6.4. Strategic initiatives
9.3.7. GE Healthcare
9.3.7.1. Company overview
9.3.7.2. Financial performance
9.3.7.3. Product benchmarking
9.3.7.4. Strategic initiatives
9.3.8. Medtronic
9.3.8.1. Company overview
9.3.8.2. Financial performance
9.3.8.3. Product benchmarking
9.3.8.4. Strategic initiatives
9.3.9. Oracle
9.3.9.1. Company overview
9.3.9.2. Financial performance
9.3.9.3. Product benchmarking
9.3.9.4. Strategic initiatives
9.3.10. Medidata
9.3.10.1. Company overview
9.3.10.2. Financial performance
9.3.10.3. Product benchmarking
9.3.10.4. Strategic initiatives
9.3.11. Google
9.3.11.1. Company overview
9.3.11.2. Financial performance
9.3.11.3. Product benchmarking
9.3.11.4. Strategic initiatives
9.3.12. IQVIA
9.3.12.1. Company overview
9.3.12.2. Financial performance
9.3.12.3. Product benchmarking
9.3.12.4. Strategic initiatives
List of Tables
Table 1 List of Abbreviation
Table 2 North America AI in Healthcare Market, By region, 2018 - 2030 (USD Million)
Table 3 North America AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 4 North America AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 5 North America AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 6 North America AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 7 U.S. AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 8 U.S. AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 9 U.S. AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 10 U.S. AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 11 Canada AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 12 Canada AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 13 U.S. AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 14 Canada AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 15 Europe AI in Healthcare Market, By region, 2018 - 2030 (USD Million)
Table 16 Europe AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 17 Europe AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 18 U.S. AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 19 Europe AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 20 Germany AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 21 Germany AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 22 U.S. AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 23 Germany AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 24 UK AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 25 UK AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 26 UK AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 27 UK AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 28 France AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 29 France AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 30 France AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 31 France AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 32 Italy AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 33 Italy AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 34 Italy AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 35 Italy AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 36 Spain AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 37 Spain AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 38 Spain AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 39 Spain AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 40 Sweden AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 41 Sweden AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 42 Sweden AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 43 Sweden AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 44 Denmark AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 45 Denmark AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 46 Denmark AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 47 Denmark AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 48 Norway AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 49 Norway AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 50 Norway AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 51 Norway AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 52 Russia AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 53 Russia AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 54 Russia AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 55 Russia AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 56 Asia Pacific AI in Healthcare Market, By region, 2018 - 2030 (USD Million)
Table 57 Asia Pacific AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 58 Asia Pacific AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 59 Asia Pacific AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 60 Asia Pacific AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 61 China AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 62 China AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 63 China AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 64 China AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 65 Japan AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 66 Japan AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 67 Japan AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 68 Japan AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 69 India AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 70 India AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 71 India AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 72 India AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 73 Singapore AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 74 Singapore AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 75 Singapore AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 76 Singapore AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 77 Australia AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 78 Australia AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 79 Australia AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 80 Australia AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 81 South Korea AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 82 South Korea AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 83 South Korea AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 84 South Korea AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 85 Thailand AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 86 Thailand AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 87 Thailand AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 88 Thailand AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 89 Latin America AI in Healthcare Market, By region, 2018 - 2030 (USD Million)
Table 90 Latin America AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 91 Latin America AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 92 Latin America AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 93 Latin America AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 94 Brazil AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 95 Brazil AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 96 Brazil AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 97 Brazil AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 98 Mexico AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 99 Mexico AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 100 Mexico AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 101 Mexico AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 102 Argentina AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 103 Argentina AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 104 Argentina AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 105 Argentina AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 106 MEA AI in Healthcare Market, By region, 2018 - 2030 (USD Million)
Table 107 MEA AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 108 MEA AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 109 MEA AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 110 MEA AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 111 South Africa AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 112 South Africa AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 113 South Africa AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 114 South Africa AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 115 Saudi Arabia AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 116 Saudi Arabia AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 117 Saudi Arabia AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 118 Saudi Arabia AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 119 UAE AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 120 UAE AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 121 UAE AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 122 UAE AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 123 Kuwait AI in Healthcare Market, By Components, 2018 - 2030 (USD Million)
Table 124 Kuwait AI in Healthcare Market, By Application, 2018 - 2030 (USD Million)
Table 125 Kuwait AI in Healthcare Market, By Technology, 2018 - 2030 (USD Million)
Table 126 Kuwait AI in Healthcare Market, By End-Use, 2018 - 2030 (USD Million)
Table 127 List of other players
Table 128 Participant’s overview
Table 129 Financial performance
Table 130 Key companies undergoing expansions
Table 131 Key companies undergoing acquisitions
Table 132 Key companies undergoing collaborations
Table 133 Key companies launching new components/services
Table 134 Key companies undergoing partnerships
Table 135 Key companies undertaking other strategies
List of Figures
Fig. 1 Market research process
Fig. 2 Data triangulation techniques
Fig. 3 Primary research pattern
Fig. 4 Primary interviews
Fig. 5 Market research approaches
Fig. 6 Value-chain-based sizing & forecasting
Fig. 7 QFD modeling for market share assessment
Fig. 8 Market formulation & validation
Fig. 9 AI in Healthcare market: market outlook
Fig. 10 AI In Healthcare competitive insights
Fig. 11 Parent market outlook
Fig. 12 Related/ancillary market outlook
Fig. 13 Penetration and growth prospect mapping
Fig. 14 Industry value chain analysis
Fig. 15 AI in Healthcare market driver impact
Fig. 16 AI in Healthcare market restraint impact
Fig. 17 AI in Healthcare market strategic initiatives analysis
Fig. 18 AI in Healthcare market: Components movement analysis
Fig. 19 AI in Healthcare market: Components outlook and key takeaways
Fig. 20 Software Solutions market estimates and forecast, 2018 - 2030
Fig. 21 Hradware management estimates and forecast, 2018 - 2030
Fig. 22 Services estimates and forecast, 2018 - 2030
Fig. 23 AI in Healthcare market: Application movement analysis
Fig. 24 AI in Healthcare market: Application outlook and key takeaways
Fig. 25 Robot assisted surgery market estimates and forecast, 2018 - 2030
Fig. 26 Virtual assistants market estimates and forecast, 2018 - 2030
Fig. 27 Administrative workflow assistants market estimates and forecast, 2018 - 2030
Fig. 28 Connected medical devices market estimates and forecast, 2018 - 2030
Fig. 29 Medical imaging & diagnostics market estimates and forecast, 2018 - 2030
Fig. 30 Clinical trials market estimates and forecast, 2018 - 2030
Fig. 31 Fraud detection market estimates and forecast, 2018 - 2030
Fig. 32 Cybersecurity market estimates and forecast, 2018 - 2030
Fig. 33 Dosage error reduction market estimates and forecast, 2018 - 2030
Fig. 34 Precision medicine market estimates and forecast, 2018 - 2030
Fig. 35 Drug discovery & developments market estimates and forecast, 2018 - 2030
Fig. 36 Lifestyle management & remote patient monitoring market estimates and forecast, 2018 - 2030
Fig. 37 Wearables market estimates and forecast, 2018 - 2030
Fig. 38 Others market estimates and forecast, 2018 - 2030
Fig. 39 AI in Healthcare market: End-User movement analysis
Fig. 40 AI in Healthcare market: End-User outlook and key takeaways
Fig. 41 Healthcare providers (hospitals, outpatient facilities, and others) market estimates and forecast, 2018 - 2030
Fig. 42 Healthcare payers market estimates and forecast, 2018 - 2030
Fig. 43 Healthcare Companies market estimates and forecast, 2018 - 2030
Fig. 44 Patients market estimates and forecast, 2018 - 2030
Fig. 45 Others market estimates and forecast, 2018 - 2030
Fig. 46 AI in Healthcare market: Technology movement analysis
Fig. 47 AI in Healthcare market: Technology outlook and key takeaways
Fig. 48 Machine learning market estimates and forecast, 2018 - 2030
Fig. 49 NLP market estimates and forecast, 2018 - 2030
Fig. 50 Context-aware computiing market estimates and forecast, 2018 - 2030
Fig. 51 Computer vision market estimates and forecast, 2018 - 2030
Fig. 52 Global AI in Healthcare market: regional movement analysis
Fig. 53 Global AI in Healthcare market: regional outlook and key takeaways
Fig. 54 Global AI in Healthcare market share and leading players
Fig. 55 North America, by country
Fig. 56 North America market estimates and forecast, 2018 - 2030
Fig. 57 U.S. market estimates and forecast, 2018 - 2030
Fig. 58 Canada market estimates and forecast, 2018 - 2030
Fig. 59 Europe market estimates and forecast, 2018 - 2030
Fig. 60 UK market estimates and forecast, 2018 - 2030
Fig. 61 Germany market estimates and forecast, 2018 - 2030
Fig. 62 France market estimates and forecast, 2018 - 2030
Fig. 63 Italy market estimates and forecast, 2018 - 2030
Fig. 64 Spain market estimates and forecast, 2018 - 2030
Fig. 65 Sweden market estimates and forecast, 2018 - 2030
Fig. 66 Denmark market estimates and forecast, 2018 - 2030
Fig. 67 Norway market estimates and forecast, 2018 - 2030
Fig. 68 Russia market estimates and forecast, 2018 - 2030
Fig. 69 Asia Pacific market estimates and forecast, 2018 - 2030
Fig. 70 China market estimates and forecast, 2018 - 2030
Fig. 71 Japan market estimates and forecast, 2018 - 2030
Fig. 72 India market estimates and forecast, 2018 - 2030
Fig. 73 Australia market estimates and forecast, 2018 - 2030
Fig. 74 South Korea market estimates and forecast, 2018 - 2030
Fig. 75 Singapore market estimates and forecast, 2018 - 2030
Fig. 76 Thailand market estimates and forecast, 2018 - 2030
Fig. 77 Latin America market estimates and forecast, 2018 - 2030
Fig. 78 Brazil market estimates and forecast, 2018 - 2030
Fig. 79 Mexico market estimates and forecast, 2018 - 2030
Fig. 80 Argentina market estimates and forecast, 2018 - 2030
Fig. 81 Middle East and Africa market estimates and forecast, 2018 - 2030
Fig. 82 South Africa market estimates and forecast, 2018 - 2030
Fig. 83 Saudi Arabia market estimates and forecast, 2018 - 2030
Fig. 84 UAE market estimates and forecast, 2018 - 2030
Fig. 85 Kuwait market estimates and forecast, 2018 - 2030
Fig. 86 Market share of key market players- AI in Healthcare market
Market Segmentation
The shortage of public health workforce has become a major concern in many countries around the world. This can mainly be attributed to the growing demand for physicians, which is higher than the supply of physicians. According to WHO, in 2019, there was a shortage of approximately 4.3 million nurses, doctors, and other healthcare professionals globally. In addition, the organization also predicts a shortfall of 15 million healthcare workers globally by 2030. As per a report published by the Association of American Medical Colleges (AAMC) in April 2019, the U.S. is anticipated to face a shortage of nearly 46,900 to 121,900 physicians by 2032. In the UK, the deficit is expected to be around 190,000 clinicians by 2027 and India already has a deficit of approximately 600,000 doctors and 2 million nurses. Globally, there have been several reforms to reduce the demand and supply gap. Easy practice policies for international medical graduates, faster physician licensing process, and increase in access to affordable medical facilities are among the few initiatives expected to reduce this gap to some extent. In addition, introduction of AI technologies in healthcare industry is expected to save millions of dollars. According to Accenture, with AI implementation, the U.S. can save nearly USD 150 billion by 2026 in healthcare industry.
Established countries, such as the U.S., Canada, Australia, and the UK, expend a large share of their GDP on healthcare facilities. In these nations, the cost and demand for care is rising promptly, therefore surging the requirement for digital technologies. In past years, the UK and the U.S. have implemented AI technologies to decrease the cost of care and enhance clinical services. In the U.S., AI has been adopted mainly due to shift to value-based care systems. In 2017, NHS deployed AI-based chatbots on the basis of trial in order to reduce the pressure on emergency triage procedure. Analytics coupled with AI technologies can significantly help in data mining of medical records, which may help in building an effective platform. AI technology is in early introduction phase and already has numerous applications in healthcare segments such as automated imaging, drug development & designing, and AI surgical robots. Technology giants are making use of past patient data, both structured and unstructured, by storing medical records. Furthermore, numerous national companies are investing in AI space by merging with smaller technology companies, which represents the growth potential of AI in the upcoming years.
Procurement of AI systems and utilizing them on a commercial scale requires high investment. In 2018, a study projected that the cost of integrating AI in healthcare globally is expected to be approximately USD 36 billion. The cost of these systems is high due to the use of advanced technology and infrastructure required to support these systems. The price of the first IBM Watson system, which was showcased in the 2011 Jeopardy show, was estimated to be nearly USD 3 million and this accounts only for the cost of hardware components. The overall cost of the system, including cloud storage and other infrastructure, is expected to be much higher than USD 3 million. The potential end users of these systems are large-sized hospitals and pharmaceutical companies & other healthcare companies. Currently, these systems are less affordable, which may impede market growth, however, increase in adoption is expected to lower their cost.
This section will provide insights into the contents included in this AI in healthcare market report and help gain clarity on the structure of the report to assist readers in navigating smoothly.
Industry overview
Industry trends
Market drivers and restraints
Market size
Growth prospects
Porter’s analysis
PESTEL analysis
Key market opportunities prioritized
Competitive landscape
Company overview
Financial performance
Product benchmarking
Latest strategic developments
Market size, estimates, and forecast from 2018 to 2030
Market estimates and forecast for product segments up to 2030
Regional market size and forecast for product segments up to 2030
Market estimates and forecast for application segments up to 2030
Regional market size and forecast for application segments up to 2030
Company financial performance
A three-pronged approach was followed for deducing the AI in healthcare market estimates and forecasts. The process has three steps: information procurement, analysis, and validation. The whole process is cyclical, and steps repeat until the estimates are validated. The three steps are explained in detail below:
Information procurement: Information procurement is one of the most extensive and important stages in our research process, and quality data is critical for accurate analysis. We followed a multi-channel data collection process for AI in healthcare market to gather the most reliable and current information possible.
Analysis: We mine the data collected to establish baselines for forecasting, identify trends and opportunities, gain insight into consumer demographics and drivers, and so much more. We utilized different methods of AI in healthcare market data depending on the type of information we’re trying to uncover in our research.
Market Research Efforts: Bottom-up Approach for estimating and forecasting demand size and opportunity, top-down Approach for new product forecasting and penetration, and combined approach of both Bottom-up and Top-down for full coverage analysis.
Value-Chain-Based Sizing & Forecasting: Supply-side estimates for understanding potential revenue through competitive benchmarking, forecasting, and penetration modeling.
Demand-side estimates for identifying parent and ancillary markets, segment modeling, and heuristic forecasting.
Qualitative Functional Deployment (QFD) Modelling for market share assessment.
Market formulation and validation: We mine the data collected to establish baselines for forecasting, identify trends and opportunities, gain insight into consumer demographics and drivers, and so much more. We utilize different methods of data analysis depending on the type of information we’re trying to uncover in our research.
Market Formulation: This step involves the finalization of market numbers. This step on an internal level is designed to manage outputs from the Data Analysis step.
Data Normalization: The final market estimates and forecasts are then aligned and sent to industry experts, in-panel quality control managers for validation.
This step also entails the finalization of the report scope and data representation pattern.
Validation: The process entails multiple levels of validation. All these steps run in parallel, and the study is forwarded for publishing only if all three levels render validated results.
The AI in healthcare market was categorized into Five segments, namely Component (Hardware, Software Solutions, Services), application (Robot-assisted Surgery, Virtual Assistants, Administrative Workflow Assistants, Connected Medical Devices, Medical Imaging & Diagnostics, Clinical Trials, Fraud Detection, Cybersecurity, Dosage Error Reduction, Precision Medicine, Drug Discovery & Development, Lifestyle Management & Remote Patient Monitoring, Wearables), technology (Machine Learning, Natural Language Processing, Context-aware Computing, Computer Vision), end-user (Healthcare Providers, Healthcare Payers, Healthcare Companies, Patients), and region (North America, Europe, Asia Pacific, Latin America, Midle East Africa).
The AI in healthcare market was segmented into component, application, technology, end-user and regions. The demand at a segment level was deduced using a funnel method. Concepts like the TAM, SAM, SOM, etc., were put into practice to understand the demand. We at GVR deploy three methods to deduce market estimates and determine forecasts. These methods are explained below:
Demand estimation of each product across countries/regions summed up to from the total market.
Variable analysis for demand forecast.
Demand estimation via analyzing paid database, and company financials either via annual reports or paid database.
Primary interviews for data revalidation and insight collection.
Used extensively for new product forecasting or analyzing penetration levels.
Tool used invoice product flow and penetration models Use of regression multi-variant analysis for forecasting Involves extensive use of paid and public databases.
Primary interviews and vendor-based primary research for variable impact analysis.
The AI in healthcare market was analyzed at a regional level. The globe was divided into North America, Europe, Asia Pacific, Latin America, and MEA, keeping in focus variables like consumption patterns, export-import regulations, consumer expectations, etc. These regions were further divided into twenty-five countries, namely, the U.S.; Canada; the UK; Germany; France; Italy; Spain; Sweden; Norway; Denmark; Russia; China; India; Japan; Australia; Singapore; South Korea; Thailand; Brazil; Mexico; Argentina; South Africa; Saudi Arabia; Kuwait and UAE.
All three above-mentioned market research methodologies were applied to arrive at regional-level conclusions. The regions were then summed up to form the global market.
The AI in healthcare market was analyzed via companies operating in the sector. Analyzing these companies and cross-referencing them to the demand equation helped us validate our assumptions and conclusions. Key market players analyzed include:
IBM Corporation (IBM Watson Health) - IBM Corporation is an American multinational company that operates in various categories and provides products & services pertaining to cognitive solutions, global business services, technology services & cloud platform, and system & global financing. It provides IBM cloud solutions to healthcare stakeholders through Watson Health, which integrates both cognitive and cloud solutions to optimize performance and manage patient health. IBM Watson Health operates in six key areas—imaging, oncology & genomics, life sciences, government, value-based care, and consumers. IBM Watson has served over 100,000 patients & consumers worldwide.
Microsoft - Microsoft is a technology solutions provider that develops and offers various software, services, and solutions. It operates through six business segments and caters a wide range of services, including product development, licensing, vendor support, and cloud-based solutions. Its product offerings include operating systems, business solution applications, cross-device productivity applications, server applications, software development tools, video games, and others. Moreover, Microsoft designs and manufactures consumer electronics such as Xbox and mobiles, among others. The company operates in over 200 countries across the globe.
NVIDIA Corporation - NVIDIA Corporation functions as a visual computing company across the world. The company operates through two segments: GPU and Tegra processor. GPU segments offers processors including GeForce for mainstream PCs and PC gaming. GeForce NOW offers cloud-based game streaming service, whereas Tesla offers AI using deep learning, accelerated computing, and generalpurpose computing. Tegra processor segment offers processors that are primarily designed to allow branded platforms such as DRIVE and SHIELD. NVIDIA has several partners that have adopted NVIDIA’s AI platform, such as GE Healthcare, ImFusion, SUBTLE MEDICAL, Imagia, Nuance, ARTERYS, Infer VISION, and 12 Sigma Technologies.
Nuance Communications, Inc. - Nuance Communications, Inc. offers voice recognition and natural language understanding solutions. The company operates through four segments including Healthcare, Mobile, Enterprise, and Imaging. The company also offers AI including machine learning and cognitive sciences to create smarter, more natural experiences with technology. The company sells its technologies across the globe through dedicated sales force, e-commerce website, and also through global network of resellers, including independent software vendors, system integrators, value added resellers, distributors, vendors, hardware, and telecommunication carriers. Furthermore, the company’s healthcare customers and partners include McKesson, UPMC, Cerner, Cleveland Clinic, Siemens, and the Mayo Clinic. The company was acquired by Microsoft in March 2022.
DeepMind Technologies Limited (Alphabet Inc. - DeepMind Technologies, acquired by Google in 2014, works as a subsidiary of the Alphabet group. The company develops AI systems and is currently pushing the boundaries of AI by developing programs that can learn to solve complex programs on its own. The company launched Deepmind Health, one of the most advanced technologies in the UK. DeepMind Ethics & Society is a research unit dedicated to carry out interdisciplinary research aimed at exploring key ethical challenges facing the field of AI.
Intel Corporation - Intel Corporation offers networking, data storage, computing, and communication solutions across the globe. The company caters to various industries, such as health & life sciences, telecommunications, retail, energy, government, financial services, and media & entertainment. The company further operates through various groups including client computing, data center, internet of things, non-volatile memory solutions, programmable solutions, and all other segments. The company develops computer vision, data analysis, localization, machine learning, and mapping for technologically progressive driver assistance systems and autonomous driving. The company’s platforms are used in notebooks, systems, and desktops. The company serves original equipment & design manufacturers, industrial & communication equipment manufacturers, and cloud service providers. Intel is investing in its data-related processors and providing them to growing markets, such as data centers, 5G communications, cloud computing, AI, and autonomous driving.
Supply Side Estimates
Company revenue estimation via referring to annual reports, investor presentations, and Hoover’s.
Segment revenue determination via variable analysis and penetration modeling.
Competitive benchmarking to identify market leaders and their collective revenue shares.
Forecasting via analyzing commercialization rates, pipelines, market initiatives, distribution networks, etc.
Demand side estimates
Identifying parent markets and ancillary markets
Segment penetration analysis to obtain pertinent
revenue/volume
Heuristic forecasting with the help of subject matter experts
Forecasting via variable analysis
Understanding market dynamics (in terms of drivers, restraints, & opportunities) in the countries.
Understanding trends & variables in the individual countries & their impact on growth and using analytical tools to provide high-level insights into the market dynamics and the associated growth pattern.
Understanding market estimates and forecasts (with the base year as 2023, historic information from 2018 to 2022, and forecast from 2024 to 2030). Regional estimates & forecasts for each category are available and are summed up to form the global market estimates.
The report provides market value for the base year 2023 and a yearly forecast till 2030 in terms of revenue/volume or both. The market for each of the segment outlooks has been provided on region & country basis for the above-mentioned forecast period.
The key industry dynamics, major technological trends, and application markets are evaluated to understand their impact on the demand for the forecast period. The growth rates were estimated using correlation, regression, and time-series analysis.
We have used the bottom-up approach for market sizing, analyzing key regional markets, dynamics, & trends for various products and end-users. The total market has been estimated by integrating the country markets.
All market estimates and forecasts have been validated through primary interviews with the key industry participants.
Inflation has not been accounted for to estimate and forecast the market.
Numbers may not add up due to rounding off.
Europe consists of EU-8, Central & Eastern Europe, along with the Commonwealth of Independent States (CIS).
Asia Pacific includes South Asia, East Asia, Southeast Asia, and Oceania (Australia & New Zealand).
Latin America includes Central American countries and the South American continent
Middle East includes Western Asia (as assigned by the UN Statistics Division) and the African continent.
GVR strives to procure the latest and unique information for reports directly from industry experts, which gives it a competitive edge. Quality is of utmost importance to us, therefore every year we focus on increasing our experts’ panel. Primary interviews are one of the critical steps in identifying recent market trends and scenarios. This process enables us to justify and validate our market estimates and forecasts to our clients. With more than 8,000 reports in our database, we have connected with some key opinion leaders across various domains, including healthcare, technology, consumer goods, and the chemical sector. Our process starts with identifying the right platform for a particular type of report, i.e., emails, LinkedIn, seminars, or telephonic conversation, as every report is unique and requires a differentiated approach.
We send out questionnaires to different experts from various regions/ countries, which is dependent on the following factors:
Report/Market scope: If the market study is global, we send questionnaires to industry experts across various regions, including North America, Europe, Asia Pacific, Latin America, and MEA.
Market Penetration: If the market is driven by technological advancements, population density, disease prevalence, or other factors, we identify experts and send out questionnaires based on region or country dominance.
The time to start receiving responses from industry experts varies based on how niche or well-penetrated the market is. Our reports include a detailed chapter on the KoL opinion section, which helps our clients understand the perspective of experts already in the market space.
NEED A CUSTOM REPORT?
We can customize every report - free of charge - including purchasing stand-alone sections or country-level reports, as well as offer affordable discounts for start-ups & universities. Contact us now
We are GDPR and CCPA compliant! Your transaction & personal information is safe and secure. For more details, please read our privacy policy.
"The quality of research they have done for us has been excellent."